Mechanics & Industry
Volume 20, Number 8, 2019
Selected scientific topics in recent applied engineering – 20 Years of the ‘French Association of Mechanics – AFM’
|Number of page(s)||16|
|Published online||25 February 2020|
Advanced model order reduction and artificial intelligence techniques empowering advanced structural mechanics simulations: application to crash test analyses
Gestamp Autotech Engineering France, 17-19, Rue Jeanne Braconnier, 92360 Meudon, France
2 ESI Group Chair @ PIMM Laboratory, Arts et Métiers ParisTech, 151 Boulevard de l’Hôpital, 75013 Paris, France
3 ESI Group, Batiment Seville, 3 bis Saarinen, 50468 Rungis, France
* e-mail: firstname.lastname@example.org
Accepted: 2 July 2019
This paper proposes a general framework for expressing parametrically quantities of interest related to the solution of complex structural mechanics models, in particular the ones involved in crash analyses where strongly coupled nonlinear and dynamic behaviors coexist with space-time localized mechanisms. Advanced nonlinear regressions able to proceed in the low-data limit, enabling to accommodate heterogeneous parameters, will be proposed and their performances evaluated in the case of crash simulations. As soon as these parametric expressions will be determined, they can be used for generating large amounts of realizations of the quantity of interest for different choices of the parameters, for supporting data-analytics. On the other hand, such parametric representations allow the use advanced optimization techniques, evaluate sensitivities and propagate uncertainty all them under the stringent real-time constraint.
© V. Limousin et al., published by EDP Sciences 2020
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